The Data Exchange Podcast: Ameet Talwalkar on the Determined Training Platform, Neural Architecture Search, Federated Learning and more.
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In this episode of the Data Exchange I speak with Ameet Talwalkar, co-founder and Chief Scientist at Determined AI1, and an Assistant Professor in the Machine Learning Department at Carnegie Mellon University. A few months ago, I spoke with one of Ameet’s co-founders (Evan Sparks), around the time they announced that they were open sourcing the Determined Training Platform (DTP). Ameet and I started off by discussing the first few months of DTP as an open source project, specifically initial feedback from users, applications and use cases that they are seeing, and much more.
We then spoke at length about Ameet’s research interests and projects at CMU. This includes:
- Hyperparameter tuning and neural architecture search
- Privacy-preserving tools, including federated learning
- Ethics and fairness in machine learning
- Democratizing machine learning
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- Evan Sparks: “An open source platform for training deep learning models”
- Matthew Honnibal: “Building open source developer tools for language applications”
- David Talby: “Building domain specific natural language applications”
- Morten Dahl: “The state of privacy-preserving machine learning”
- Harish Doddi: “Understanding machine learning model governance”
- Chris Nicholson: “Next-generation simulation software will incorporate deep reinforcement learning”
- NLP in industry survey: We want to find out how people are using NLP, what tools they are using, and what challenges they face. Please take 5 minutes to fill out our survey and pass it along to your friends and colleagues.
 I am an advisor to Determined AI.
[Image: Abu Dhabi, Hyatt Capital Gate by Ben Lorica.]
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